Neural networks promise to bring robust, quantitative analysis to medical fields. However, their adoption is limited by the technicalities of training these networks and the required volume and ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...